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Recommending an Insurance Policy Using Association Rule Mining
Nilkamal P.More ; Suchitra Patil
Data mining
Year: 2014, Volume:1, Issue : 4
Pages: 70 - 73
Improving the efficiency of ascertaining the frequent itemsets is a crucial issue in association rule mining algorithms. This paper illustrates the use of Apriori algorithm for Life Insurance Corporation for recommending a policy to a customer who is interested in taking a policy. For recommending a policy to a customer, the information about existing policy holders is taken into consideration. This paper also analyzes the performance of “An Improved Apriori Algorithm based on Matrix†[1].
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An Energy Efficient Cluster Head Selection Algorithm for Wireless Sensor Networks
MANGLESH KHANDELWAL ; Gajendra Singh Chandel; Kailash Patidar
Computer science & Engineering
Year: 2014, Volume:1, Issue : 4
Pages: 74 - 79
The Cluster-head Gateway Switch Routing protocol (CGSR) uses a hierarchical network topology. CGSR organizes nodes into clusters, with coordination among the members of each cluster entrusted to a special node named cluster-head. The cluster head selection is done with the help of any of the algorithm for cluster head selection. Energy is the primary constraint on designing any Wireless Networks practically. This leads to limited network lifetime of network. Low-Energy Adaptive Clustering Hierarchy (LEACH) and LEACH with deterministic cluster head selection are some of the cluster head algorithms that enable to optimize power consumption of WSN. There are various factors like density & distance, threshold based, power efficient. Load balancing and scalability are the other factors which plays important role in the selection of Cluster head. Algorithms based on load balancing reduce communication cost to a great extent. The algorithms that this study is focused are A Density and Distance based Cluster Head, An Energy Efficient Algorithm for Cluster-Head Selection in WSNs, Consumed Energy as a Factor for Cluster Head. These three algorithms are analyzed and studied in this paper. The analysis of these algorithms gave birth to a new algorithm called EDRLEACH, which is proposed through this paper.
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Recommendation of Books Using Improved Apriori Algorithm
Nilkamal P. More
Data mining
Year: 2014, Volume:1, Issue : 4
Pages: 80 - 82
Association rule mining is a data mining technique. It is used for finding the items from a transaction list which occur together frequently. Some of the algorithms which are used most popularly for association rule mining are i) Apriori algorithm ii) FP-tree algorithm.
This paper researches on use of modern algorithm Apriori for book shop for recommending a book to a customer who wants to buy a book based on the information that is maintained in the transaction database. The result of this compared with other algorithm available for association rule mining.
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An Approach to Classify the Object from the Satellite Image using Image Analysis Tool
Parivallal R. ; Dhivya Bharathi L.; Elang K.; Karthik T.; Nagarajan B.
Computer Applications, Image processing
Year: 2014, Volume:1, Issue : 4
Pages: 83 - 87
Building objects area classification is one of the main procedures used in updating digital maps and geographic information system databases. It is an active research field in computer vision and remote sensing. Full automatic systems in this field are not yet operational and cannot be implemented in a single step. In this paper, we present a semi-automatic building object classification using Envi tool, object-based classification in Google map images applied to Sathyamangalam city (INDIA). The Envi tool, object-based classification approach follows the standard scheme of object-based image classification, which is discussed in this paper. The results obtained show an overall objects (like building, trees and roads) area detection of good percentage, when the parameters are properly adjusted and adapted to the type of areas considered.
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PID Controller Tuning Methods Comparison with Particle Swarm Optimization for FOPTD System
K. Mohamed Hussain ; R. Allwyn Rajendran Zepherin; M. Shantha Kumar; S. M. Giriraj Kumar
Instrumentation and Control Engineering
Year: 2014, Volume:1, Issue : 4
Pages: 88 - 93
Temperature Measurement is one of the major controlling parameters in all process industries. A closed loop system is formed by connecting a controller with that process with the combination of various transducers leading to stability. This paper deals with comparison of various PID control tuning techniques and Particle Swarm Optimization (PSO) technique. A single input single output (SISO) Real Time system is taken and Transfer function is identified. Control Transfer Function for the Transfer Function has been determined. Control parameters such as Proportional Gain, Time and Derivative Time are observed and tabulated. Performance indices such as Integral Square Error (ISE), Integral Absolute Error (IAE), Integral Time Absolute Error (ITAE), Mean Square Error (MSE) have been simulated. Comparison between PID Controller, Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) has been carried out to determine the best controller for the temperature system.
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Abstract
